



import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging


a      :  str			     =			logging.get_logger(__name__)

a      :  Any			     =			'▁'

a      :  Optional[int]			     =			{'vocab_file': 'sentencepiece.bpe.model'}

a      :  Optional[int]			     =			{
    'vocab_file': {
        'facebook/nllb-200-distilled-600M': (
            'https://huggingface.co/facebook/nllb-200-distilled-600M/blob/main/sentencepiece.bpe.model'
        ),
    }
}

a      :  List[Any]			     =			{
    'facebook/nllb-200-distilled-600M': 1_024,
}

# fmt: off
a      :  int			     =			['ace_Arab', 'ace_Latn', 'acm_Arab', 'acq_Arab', 'aeb_Arab', 'afr_Latn', 'ajp_Arab', 'aka_Latn', 'amh_Ethi', 'apc_Arab', 'arb_Arab', 'ars_Arab', 'ary_Arab', 'arz_Arab', 'asm_Beng', 'ast_Latn', 'awa_Deva', 'ayr_Latn', 'azb_Arab', 'azj_Latn', 'bak_Cyrl', 'bam_Latn', 'ban_Latn', 'bel_Cyrl', 'bem_Latn', 'ben_Beng', 'bho_Deva', 'bjn_Arab', 'bjn_Latn', 'bod_Tibt', 'bos_Latn', 'bug_Latn', 'bul_Cyrl', 'cat_Latn', 'ceb_Latn', 'ces_Latn', 'cjk_Latn', 'ckb_Arab', 'crh_Latn', 'cym_Latn', 'dan_Latn', 'deu_Latn', 'dik_Latn', 'dyu_Latn', 'dzo_Tibt', 'ell_Grek', 'eng_Latn', 'epo_Latn', 'est_Latn', 'eus_Latn', 'ewe_Latn', 'fao_Latn', 'pes_Arab', 'fij_Latn', 'fin_Latn', 'fon_Latn', 'fra_Latn', 'fur_Latn', 'fuv_Latn', 'gla_Latn', 'gle_Latn', 'glg_Latn', 'grn_Latn', 'guj_Gujr', 'hat_Latn', 'hau_Latn', 'heb_Hebr', 'hin_Deva', 'hne_Deva', 'hrv_Latn', 'hun_Latn', 'hye_Armn', 'ibo_Latn', 'ilo_Latn', 'ind_Latn', 'isl_Latn', 'ita_Latn', 'jav_Latn', 'jpn_Jpan', 'kab_Latn', 'kac_Latn', 'kam_Latn', 'kan_Knda', 'kas_Arab', 'kas_Deva', 'kat_Geor', 'knc_Arab', 'knc_Latn', 'kaz_Cyrl', 'kbp_Latn', 'kea_Latn', 'khm_Khmr', 'kik_Latn', 'kin_Latn', 'kir_Cyrl', 'kmb_Latn', 'kon_Latn', 'kor_Hang', 'kmr_Latn', 'lao_Laoo', 'lvs_Latn', 'lij_Latn', 'lim_Latn', 'lin_Latn', 'lit_Latn', 'lmo_Latn', 'ltg_Latn', 'ltz_Latn', 'lua_Latn', 'lug_Latn', 'luo_Latn', 'lus_Latn', 'mag_Deva', 'mai_Deva', 'mal_Mlym', 'mar_Deva', 'min_Latn', 'mkd_Cyrl', 'plt_Latn', 'mlt_Latn', 'mni_Beng', 'khk_Cyrl', 'mos_Latn', 'mri_Latn', 'zsm_Latn', 'mya_Mymr', 'nld_Latn', 'nno_Latn', 'nob_Latn', 'npi_Deva', 'nso_Latn', 'nus_Latn', 'nya_Latn', 'oci_Latn', 'gaz_Latn', 'ory_Orya', 'pag_Latn', 'pan_Guru', 'pap_Latn', 'pol_Latn', 'por_Latn', 'prs_Arab', 'pbt_Arab', 'quy_Latn', 'ron_Latn', 'run_Latn', 'rus_Cyrl', 'sag_Latn', 'san_Deva', 'sat_Beng', 'scn_Latn', 'shn_Mymr', 'sin_Sinh', 'slk_Latn', 'slv_Latn', 'smo_Latn', 'sna_Latn', 'snd_Arab', 'som_Latn', 'sot_Latn', 'spa_Latn', 'als_Latn', 'srd_Latn', 'srp_Cyrl', 'ssw_Latn', 'sun_Latn', 'swe_Latn', 'swh_Latn', 'szl_Latn', 'tam_Taml', 'tat_Cyrl', 'tel_Telu', 'tgk_Cyrl', 'tgl_Latn', 'tha_Thai', 'tir_Ethi', 'taq_Latn', 'taq_Tfng', 'tpi_Latn', 'tsn_Latn', 'tso_Latn', 'tuk_Latn', 'tum_Latn', 'tur_Latn', 'twi_Latn', 'tzm_Tfng', 'uig_Arab', 'ukr_Cyrl', 'umb_Latn', 'urd_Arab', 'uzn_Latn', 'vec_Latn', 'vie_Latn', 'war_Latn', 'wol_Latn', 'xho_Latn', 'ydd_Hebr', 'yor_Latn', 'yue_Hant', 'zho_Hans', 'zho_Hant', 'zul_Latn']







class 				_a				(   _lowerCAmelCase					):
			A      		=	VOCAB_FILES_NAMES
			A      		=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			A      		=	PRETRAINED_VOCAB_FILES_MAP
			A      		=	['''input_ids''', '''attention_mask''']

			A      		=	[]
			A      		=	[]

			def __init__(self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_="<s>",   SCREAMING_SNAKE_CASE_="</s>",   SCREAMING_SNAKE_CASE_="</s>",   SCREAMING_SNAKE_CASE_="<s>",   SCREAMING_SNAKE_CASE_="<unk>",   SCREAMING_SNAKE_CASE_="<pad>",   SCREAMING_SNAKE_CASE_="<mask>",   SCREAMING_SNAKE_CASE_=None,   SCREAMING_SNAKE_CASE_=None,   SCREAMING_SNAKE_CASE_=None,   SCREAMING_SNAKE_CASE_ = None,   SCREAMING_SNAKE_CASE_=None,   SCREAMING_SNAKE_CASE_=False,   **SCREAMING_SNAKE_CASE_,   )       ->   Any:
						# Mask token behave like a normal word, i.e. include the space before it
						UpperCAmelCase_:		List[Any]							      =     AddedToken(SCREAMING_SNAKE_CASE_,   lstrip=SCREAMING_SNAKE_CASE_,   rstrip=SCREAMING_SNAKE_CASE_					) if isinstance(SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_					) else mask_token

						UpperCAmelCase_:		Optional[int]							      =     {} if sp_model_kwargs is None else sp_model_kwargs
						UpperCAmelCase_:		Tuple							      =     legacy_behaviour

						super().__init__(
						    bos_token=SCREAMING_SNAKE_CASE_,   eos_token=SCREAMING_SNAKE_CASE_,   unk_token=SCREAMING_SNAKE_CASE_,   sep_token=SCREAMING_SNAKE_CASE_,   cls_token=SCREAMING_SNAKE_CASE_,   pad_token=SCREAMING_SNAKE_CASE_,   mask_token=SCREAMING_SNAKE_CASE_,   tokenizer_file=SCREAMING_SNAKE_CASE_,   src_lang=SCREAMING_SNAKE_CASE_,   tgt_lang=SCREAMING_SNAKE_CASE_,   additional_special_tokens=SCREAMING_SNAKE_CASE_,   sp_model_kwargs=self.sp_model_kwargs,   legacy_behaviour=SCREAMING_SNAKE_CASE_,   **SCREAMING_SNAKE_CASE_,   )

						UpperCAmelCase_:		str							      =     spm.SentencePieceProcessor(**self.sp_model_kwargs					)
						self.sp_model.Load(str(SCREAMING_SNAKE_CASE_					)					)
						UpperCAmelCase_:		Optional[Any]							      =     vocab_file
						# Original fairseq vocab and spm vocab must be "aligned":
						# Vocab    |    0    |    1    |   2    |    3    |  4   |  5   |  6   |   7  |   8  |  9
						# -------- | ------- | ------- | ------ | ------- | ---- | ---- | ---- | ---- | ---- | ----
						# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | 'an' | '▁n' | '▁m' | '▁t' | '▁k' | '▁a'
						# spm      | '<unk>' | '<s>'   | '</s>' | 'an'    | '▁n' | '▁m' | '▁t' | '▁k' | '▁a' | '▁s'

						# Mimic fairseq token-to-id alignment for the first 4 token
						UpperCAmelCase_:		Tuple							      =     {"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

						# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
						UpperCAmelCase_:		Optional[Any]							      =     1

						UpperCAmelCase_:		Any							      =     len(self.sp_model					)
						UpperCAmelCase_:		int							      =     {
						    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(SCREAMING_SNAKE_CASE_					)
						}
						UpperCAmelCase_:		Optional[Any]							      =     {v: k for k, v in self.lang_code_to_id.items()}
						UpperCAmelCase_:		List[str]							      =     len(self.sp_model					) + len(self.lang_code_to_id					) + self.fairseq_offset

						self.fairseq_tokens_to_ids.update(self.lang_code_to_id					)
						UpperCAmelCase_:		List[str]							      =     {v: k for k, v in self.fairseq_tokens_to_ids.items()}
						UpperCAmelCase_:		Tuple							      =     list(self.lang_code_to_id.keys()					)

						if additional_special_tokens is not None:
									# Only add those special tokens if they are not already there.
									self._additional_special_tokens.extend(
									    [t for t in additional_special_tokens if t not in self._additional_special_tokens]					)

						UpperCAmelCase_:		str							      =     src_lang if src_lang is not None else """eng_Latn"""
						UpperCAmelCase_:		List[str]							      =     self.lang_code_to_id[self._src_lang]
						UpperCAmelCase_:		Any							      =     tgt_lang
						self.set_src_lang_special_tokens(self._src_lang					)

			def __getstate__(self					)       ->   str:
						UpperCAmelCase_:		Union[str, Any]							      =     self.__dict__.copy()
						UpperCAmelCase_:		List[Any]							      =     None
						UpperCAmelCase_:		Optional[int]							      =     self.sp_model.serialized_model_proto()
						return state

			def __setstate__(self,   SCREAMING_SNAKE_CASE_					)       ->   Optional[int]:
						UpperCAmelCase_:		List[str]							      =     d

						# for backward compatibility
						if not hasattr(self,   """sp_model_kwargs"""					):
									UpperCAmelCase_:		Dict							      =     {}

						UpperCAmelCase_:		Optional[Any]							      =     spm.SentencePieceProcessor(**self.sp_model_kwargs					)
						self.sp_model.LoadFromSerializedProto(self.sp_model_proto					)

			@property
			def      __snake_case       (self					)       ->   Any:
						return len(self.sp_model					) + len(self.lang_code_to_id					) + self.fairseq_offset + 1  # Plus 1 for the mask token

			@property
			def      __snake_case       (self					)       ->   str:
						return self._src_lang

			@src_lang.setter
			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_					)       ->   None:
						UpperCAmelCase_:		List[str]							      =     new_src_lang
						self.set_src_lang_special_tokens(self._src_lang					)

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_ = None,   SCREAMING_SNAKE_CASE_ = False					)       ->   List[int]:

						if already_has_special_tokens:
									return super().get_special_tokens_mask(
									    token_ids_a=SCREAMING_SNAKE_CASE_,   token_ids_a=SCREAMING_SNAKE_CASE_,   already_has_special_tokens=SCREAMING_SNAKE_CASE_					)

						UpperCAmelCase_:		Optional[int]							      =     [1] * len(self.prefix_tokens					)
						UpperCAmelCase_:		Optional[Any]							      =     [1] * len(self.suffix_tokens					)
						if token_ids_a is None:
									return prefix_ones + ([0] * len(SCREAMING_SNAKE_CASE_					)) + suffix_ones
						return prefix_ones + ([0] * len(SCREAMING_SNAKE_CASE_					)) + ([0] * len(SCREAMING_SNAKE_CASE_					)) + suffix_ones

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_ = None					)       ->   List[int]:
						if token_ids_a is None:
									return self.prefix_tokens + token_ids_a + self.suffix_tokens
						# We don't expect to process pairs, but leave the pair logic for API consistency
						return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_ = None					)       ->   List[int]:
						UpperCAmelCase_:		str							      =     [self.sep_token_id]
						UpperCAmelCase_:		List[Any]							      =     [self.cls_token_id]

						if token_ids_a is None:
									return len(cls + token_ids_a + sep					) * [0]
						return len(cls + token_ids_a + sep + sep + token_ids_a + sep					) * [0]

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_,   **SCREAMING_SNAKE_CASE_					)       ->   Union[str, Any]:
						if src_lang is None or tgt_lang is None:
									raise ValueError("""Translation requires a `src_lang` and a `tgt_lang` for this model"""					)
						UpperCAmelCase_:		Union[str, Any]							      =     src_lang
						UpperCAmelCase_:		Any							      =     self(SCREAMING_SNAKE_CASE_,   add_special_tokens=SCREAMING_SNAKE_CASE_,   return_tensors=SCREAMING_SNAKE_CASE_,   **SCREAMING_SNAKE_CASE_					)
						UpperCAmelCase_:		Dict							      =     self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_					)
						UpperCAmelCase_:		List[str]							      =     tgt_lang_id
						return inputs

			def      __snake_case       (self					)       ->   int:
						UpperCAmelCase_:		Dict							      =     {self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_					): i for i in range(self.vocab_size					)}
						vocab.update(self.added_tokens_encoder					)
						return vocab

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_					)       ->   List[str]:
						return self.sp_model.encode(SCREAMING_SNAKE_CASE_,   out_type=SCREAMING_SNAKE_CASE_					)

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_					)       ->   List[Any]:
						if token in self.fairseq_tokens_to_ids:
									return self.fairseq_tokens_to_ids[token]
						UpperCAmelCase_:		int							      =     self.sp_model.PieceToId(SCREAMING_SNAKE_CASE_					)

						# Need to return unknown token if the SP model returned 0
						return spm_id + self.fairseq_offset if spm_id else self.unk_token_id

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_					)       ->   Optional[Any]:
						if index in self.fairseq_ids_to_tokens:
									return self.fairseq_ids_to_tokens[index]
						return self.sp_model.IdToPiece(index - self.fairseq_offset					)

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_					)       ->   str:
						UpperCAmelCase_:		Optional[Any]							      =     """""".join(SCREAMING_SNAKE_CASE_					).replace(SCREAMING_SNAKE_CASE_,   """ """					).strip()
						return out_string

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_ = None					)       ->   Tuple[str]:
						if not os.path.isdir(SCREAMING_SNAKE_CASE_					):
									logger.error(f'Vocabulary path ({save_directory}) should be a directory'					)
									return
						UpperCAmelCase_:		List[str]							      =     os.path.join(
						    SCREAMING_SNAKE_CASE_,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]					)

						if os.path.abspath(self.vocab_file					) != os.path.abspath(SCREAMING_SNAKE_CASE_					) and os.path.isfile(self.vocab_file					):
									copyfile(self.vocab_file,   SCREAMING_SNAKE_CASE_					)
						elif not os.path.isfile(self.vocab_file					):
									with open(SCREAMING_SNAKE_CASE_,   """wb"""					) as fi:
												UpperCAmelCase_:		Union[str, Any]							      =     self.sp_model.serialized_model_proto()
												fi.write(SCREAMING_SNAKE_CASE_					)

						return (out_vocab_file,)

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_ = "eng_Latn",   SCREAMING_SNAKE_CASE_ = None,   SCREAMING_SNAKE_CASE_ = "fra_Latn",   **SCREAMING_SNAKE_CASE_,   )       ->   BatchEncoding:
						UpperCAmelCase_:		int							      =     src_lang
						UpperCAmelCase_:		str							      =     tgt_lang
						return super().prepare_seqaseq_batch(SCREAMING_SNAKE_CASE_,   SCREAMING_SNAKE_CASE_,   **SCREAMING_SNAKE_CASE_					)

			def      __snake_case       (self					)       ->   List[str]:
						return self.set_src_lang_special_tokens(self.src_lang					)

			def      __snake_case       (self					)       ->   List[str]:
						return self.set_tgt_lang_special_tokens(self.tgt_lang					)

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_					)       ->   None:
						UpperCAmelCase_:		int							      =     self.lang_code_to_id[src_lang]
						if self.legacy_behaviour:
									UpperCAmelCase_:		List[Any]							      =     []
									UpperCAmelCase_:		Optional[Any]							      =     [self.eos_token_id, self.cur_lang_code]
						else:
									UpperCAmelCase_:		Optional[Any]							      =     [self.cur_lang_code]
									UpperCAmelCase_:		Any							      =     [self.eos_token_id]

			def      __snake_case       (self,   SCREAMING_SNAKE_CASE_					)       ->   None:
						UpperCAmelCase_:		Any							      =     self.lang_code_to_id[lang]
						if self.legacy_behaviour:
									UpperCAmelCase_:		List[str]							      =     []
									UpperCAmelCase_:		List[str]							      =     [self.eos_token_id, self.cur_lang_code]
						else:
									UpperCAmelCase_:		Any							      =     [self.cur_lang_code]
									UpperCAmelCase_:		str							      =     [self.eos_token_id]











def  lowerCAmelCase_	(lowerCAmelCase__:		int  ):





			"""simple docstring"""


			if num <= 0:
						raise ValueError("""Input must be a positive integer"""  )

			UpperCAmelCase_:		Tuple							      =     [True] * (num + 1)

			UpperCAmelCase_:		Tuple							      =     2
			while p * p <= num:
						if primes[p]:
									for i in range(p * p		,						num + 1		,						lowerCAmelCase__  ):
												UpperCAmelCase_:		Optional[Any]							      =     False
						p += 1

			return [prime for prime in range(2		,						num + 1  ) if primes[prime]]


if __name__ == "__main__":
	import doctest

	doctest.testmod()

	a      :  Optional[Any]			     =			int(input('Enter a positive integer: ').strip())
	print(prime_sieve_eratosthenes(user_num))






